Review of Porcine Disease Resistance Genetic Basis Research Based on GWAS
Bibliographic record
Abstract
This study reviews the latest progress in research on the genetic basis of porcine disease resistance based on GWAS. This study first introduces the importance and challenges of porcine disease resistance to the breeding industry, as well as the history and current status of research on porcine disease resistance; Then elaborates on the role and advantages of GWAS technology in research on the genetic basis of disease resistance, including its characteristics of high-throughput, high-resolution and comprehensive detection of genetic variation; Furthermore, it focuses on the important results achieved by GWAS-based research in discovering genetic variations related to porcine disease resistance, and the impact of these variations on disease resistance. Potential influencing mechanisms of sex. This study also explores the limitations of GWAS in porcine disease resistance research, and looks at the direction and potential contributions of future research, with a view to providing more effective strategies and means for pig health management and the sustainable development of the breeding industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".